This presentation covers the challenges and trade-offs involved in managing Amazon EC2 capacity and availability. It explores various usage models, including on-demand instances, capacity reservations, capacity blocks for machine learning, and spot instances. The speakers also introduce AWS's new EC2 Capacity Manager tool to help organizations optimize their capacity utilization.
On-Demand Instances
On-demand instances provide elasticity and a pay-as-you-go model, making them suitable for stateful workloads with scaling patterns or temporary/short-term needs.
AWS does extensive forecasting and capacity planning to ensure on-demand availability, but there can still be instances where a specific instance type's pool runs low.
Flexibility is key - being able to use different instance families, generations, sizes, or CPU manufacturers can help avoid capacity shortages.
AWS provides tools like EC2 Fleet and Auto Scaling Groups to simplify managing this flexibility.
Capacity Reservations
On-Demand Capacity Reservations (ODCRs) provide assured capacity for specific instance type and availability zone combinations.
ODCRs are recommended for workloads that require deterministic performance or are so critical that capacity assurance is essential.
ODCRs can be created on-demand or for a future date to ensure capacity is available when needed.
Capacity reservation preferences in Auto Scaling Groups can help optimize ODCR utilization.
Sharing ODCRs across accounts or with lower-priority workloads can improve efficiency.
Capacity Blocks for Machine Learning
Capacity blocks provide reserved capacity for 1-26 weeks, primarily targeting GPU-accelerated or other specialized compute instances used for machine learning training.
These instances are often less flexible due to the need to compile to specific hardware architectures and the large data requirements.
Capacity blocks integrate with SageMaker to provide predictable access to accelerated compute resources.
Spot Instances
Spot instances leverage AWS's spare data center capacity, offering up to 90% discounts but with the risk of interruption.
Key strategies for using spot instances include managing the 2-minute termination notice, being flexible across instance types/sizes/generations, and leveraging spot placement scores.
Spot placement scores help identify the most stable spot capacity based on your workload requirements.
EC2 Capacity Manager
EC2 Capacity Manager is a new AWS tool that provides a unified view of an organization's EC2 capacity utilization across all usage models and accounts.
It helps identify unused capacity reservations, track spot instance interruptions, and optimize capacity allocation.
Capacity Manager can be set up at the account or organization level, providing visibility and management capabilities for large-scale EC2 deployments.
Key Takeaways
There is no one-size-fits-all EC2 usage model - organizations typically leverage a mix to optimize for cost, availability, and performance.
Flexibility, through techniques like attribute-based instance selection, is crucial for managing capacity constraints.
Capacity reservations can provide assured access but come at a higher cost, while spot instances offer significant discounts with interruption risk.
EC2 Capacity Manager simplifies capacity management at scale, enabling organizations to better optimize their EC2 utilization.
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